Machine Learning Resident - Client: Repsol (6 months)

"If you are interested in the application of reinforcement learning approaches to controlling industrial plant systems, this is the right opportunity for you. Be a part of the team of research and machine learning scientists building RL systems from the ground up and get mentored by some of the best minds in AI during the process." 

- Payam Mousavi, Applied Research Scientist

About the Role

This is a paid full-time residency that will be undertaken over a six-month period. The resident will report to an Amii Scientist and regularly consult and work with the client’s team to share insights and support knowledge transfer throughout the engagement. As part of a cross-functional project team with expertise in ML research, software engineering, project management, and industrial systems, the resident will have the opportunity to work on a technically challenging and high-impact project while being mentored by world-class scientists.

About the Client

Repsol is a global multi-energy company headquartered in Madrid, Spain, with operations spanning the entire energy value chain, from exploration and production to refining, chemicals, and low-carbon energy solutions. With a strong commitment to innovation and sustainability, Repsol has set an ambitious goal of achieving net-zero emissions by 2050. As part of its digital transformation strategy, the company is actively investing in advanced technologies such as artificial intelligence, data science, and automation to enhance operational efficiency, safety, and environmental performance across its industrial assets. This engagement supports Repsol’s broader vision by exploring the application of machine learning techniques to model complex system dynamics and optimize control strategies.

About the Project

The goal of this project is to develop data-driven robust forward models using several chemical process control datasets and/or the associated simulators for the purpose of developing controllers using RL or MPC. Our approach integrates classical nonlinear dynamical systems theory with modern machine learning techniques.  The developed models should  be integrated into the current model training and validation framework  being developed at repsol TechLab, which is an innovative in-house solution to debug, validate, derisk, analyze and operate industrial plant models. 

Required Skills / Expertise

Are you passionate about building impactful solutions? Do you want to apply cutting-edge machine learning to real-world industrial challenges? This opportunity offers the chance to grow both personally and professionally while contributing to the development of advanced control systems in a high-impact domain. We’re looking for a talented and enthusiastic individual with a strong background in machine learning, particularly in reinforcement learning and its application to complex process environments.

Key Responsibilities:

• Develop, train, and evaluate forward models using chemical process control data and simulators, using a combination of ideas from dynamical systems and modern machine learning approaches.


• Design and optimize RL and MPC models to enhance operational performance in complex industrial systems.


• Conduct applied research on ML techniques, with a focus on understanding and addressing the limitations of existing models in industrial settings.


• Prepare and curate relevant operational and control system data for ML model training and validation.


• Collaborate with the project team and client stakeholders to develop POCs and practical, domain-informed solutions.


• Engage in regular client meetings, contributing to presentations and reports on project progress and technical insights.


• Optimize ML pipelines to ensure efficiency, scalability, and compatibility with real-time industrial environments.

Required Qualifications: 

• Completion of a graduate level program or higher (M.S./Ph.D) in Computer Science, ML or Engineering


• Research or project experience in machine learning, specifically using reinforcement learning tools and techniques as well as classical control techniques such as MPC


• Proficient in Python programming language and related ML frameworks, libraries and toolkits (e.g. Scikit learn, PyTorch, Pandas)


• Familiarity with linux, Git version control, and writing clean code


• A positive attitude towards learning and understanding a new applied domain 


• Must be legally eligible to work in Canada
  

Preferred Qualifications:

• Previous exposure/experience related to industrial process control/automation and optimization


• Familiarity or experience with classical control algorithms (PID, MPC, etc.)


• Prior software engineering experience in industry (e.g., data pre-processing, PLC programming, creating/managing dashboards, databases)


• Familiarity with the refining, petrochemical, or other industrial process controls domains


• Publication record in peer-reviewed academic conferences or relevant journals in machine learning (specifically reinforcement learning or applied ML in industrial applications)

Non-Technical Requirements: 

• Desire to take ownership of a problem and demonstrated leadership skills 


• Interdisciplinary team player enthusiastic about working together to achieve excellence


• Capable of critical and independent thought


• Able to communicate technical concepts clearly and advise on the application of machine intelligence


• Intellectual curiosity and the desire to learn new things, techniques, and technologies

Why You Should Apply

Besides gaining industry experience, additional perks include:

• Work under the mentorship of an Amii Scientist for the duration of the project


• Participate in professional development activities


• Gain access to the Amii community and events


• Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)


• Build your professional network

About Amii

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

How to Apply

If this sounds like the opportunity you've been waiting for, please don’t wait for the closing July 11, 2025 to apply - we’re excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won’t be used in the selection process.